Double-Shock Compression Pathways from Diamond to BC8 Carbon.

Carbon is one of the most important elements for both industrial applications and fundamental research, including life, physics, chemistry, materials, and even planetary science. Although theoretical predictions on the transition from diamond to the BC8 (Ia3[over ¯]) carbon were made more than thirty years ago, after tremendous experimental efforts, direct evidence for the existence of BC8 carbon is still lacking. In this study, a machine learning potential was developed for high-pressure carbon fitted from first-principles calculations, which exhibited great capabilities in modeling the melting and Hugoniot line. Using the molecular dynamics based on this machine learning potential, we designed a thermodynamic pathway that is achievable for the double shock compression experiment to obtain the elusive BC8 carbon. Diamond was compressed up to 584 GPa after the first shock at 20.5 km/s. Subsequently, in the second shock compression at 24.8 or 25.0 km/s, diamond was compressed to a supercooled liquid and then solidified to BC8 in around 1 ns. Furthermore, the critical nucleus size and nucleation rate of BC8 were calculated, which are crucial for nano-second x-ray diffraction measurements to observe BC8 carbon during shock compressions. The key to obtaining BC8 carbon lies in the formation of liquid at a sufficient supercooling. Our work provides a feasible pathway by which the long-sought BC8 phase of carbon can be reached in experiments.

MAGUS: machine learning and graph theory assisted universal structure searcher.

Crystal structure predictions based on first-principles calculations have gained great success in materials science and solid state physics. However, the remaining challenges still limit their applications in systems with a large number of atoms, especially the complexity of conformational space and the cost of local optimizations for big systems. Here, we introduce a crystal structure prediction method, MAGUS, based on the evolutionary algorithm, which addresses the above challenges with machine learning and graph theory. Techniques used in the program are summarized in detail and benchmark tests are provided. With intensive tests, we demonstrate that on-the-fly machine-learning potentials can be used to significantly reduce the number of expensive first-principles calculations, and the crystal decomposition based on graph theory can efficiently decrease the required configurations in order to find the target structures. We also summarized the representative applications of this method on several research topics, including unexpected compounds in the interior of planets and their exotic states at high pressure and high temperature (superionic, plastic, partially diffusive state, etc.); new functional materials (superhard, high-energy-density, superconducting, photoelectric materials), etc. These successful applications demonstrated that MAGUS code can help to accelerate the discovery of interesting materials and phenomena, as well as the significant value of crystal structure predictions in general.

Prediction of surface reconstructions using MAGUS.

In this paper, we present a new module to predict the potential surface reconstruction configurations of given surface structures in the framework of our machine learning and graph theory assisted universal structure searcher. In addition to random structures generated with specific lattice symmetry, we made full use of bulk materials to obtain a better distribution of population energy, namely, randomly appending atoms to a surface cleaved from bulk structures or moving/removing some of the atoms on the surface, which is inspired by natural surface reconstruction processes. In addition, we borrowed ideas from cluster predictions to spread structures better between different compositions, considering that surface models of different atom numbers usually have some building blocks in common. To validate this newly developed module, we tested it with studies on the surface reconstructions of Si (100), Si (111), and 4H-SiC(11̄02)-c(2×2), respectively. We successfully gave the known ground states, as well as a new SiC surface model, in an extremely Si-rich environment.

Magnesium oxide-water compounds at megabar pressure and implications on planetary interiors.

Magnesium Oxide (MgO) and water (H2O) are abundant in the interior of planets. Their properties, and in particular their interaction, significantly affect the planet interior structure and thermal evolution. Here, using crystal structure predictions and ab initio molecular dynamics simulations, we find that MgO and H2O can react again at ultrahigh pressure, although Mg(OH)2 decomposes at low pressure. The reemergent MgO-H2O compounds are: Mg2O3H2 above 400 GPa, MgO3H4 above 600 GPa, and MgO4H6 in the pressure range of 270-600 GPa. Importantly, MgO4H6 contains 57.3 wt % of water, which is a much higher water content than any reported hydrous mineral. Our results suggest that a substantial amount of water can be stored in MgO rock in the deep interiors of Earth to Neptune mass planets. Based on molecular dynamics simulations we show that these three compounds exhibit superionic behavior at the pressure-temperature conditions as in the interiors of Uranus and Neptune. Moreover, the water-rich compound MgO4H6 could be stable inside the early Earth and therefore may serve as a possible early Earth water reservoir. Our findings, in the poorly explored megabar pressure regime, provide constraints for interior and evolution models of wet planets in our solar system and beyond.

Pressure Stabilized Lithium-Aluminum Compounds with Both Superconducting and Superionic Behaviors.

Superconducting and superionic behaviors have physically intriguing dynamic properties of electrons and ions, respectively, both of which are conceptually important and have great potential for practical applications. Whether these two phenomena can appear in the same system is an interesting and important question. Here, using crystal structure predictions and first-principle calculations combined with machine learning, we identify several stable Li-Al compounds with electride behavior under high pressure, and we find that the electronic density of states of some of the compounds has characteristics of the two-dimensional electron gas. Among them, we estimate that Li_{6}Al at 150 GPa has a superconducting transition temperature of around 29 K and enters a superionic state at a high temperature and wide pressure range. The diffusion in Li_{6}Al is found to be affected by an electride and attributed to the atomic collective motion. Our results indicate that alkali metal alloys can be effective platforms to study the abundant physical properties and their manipulation with pressure and temperature.

Metallic Aluminum Suboxides with Ultrahigh Electrical Conductivity at High Pressure.

Aluminum, as the most abundant metallic elemental content in the Earth's crust, usually exists in the form of alumina (Al2O3). However, the oxidation state of aluminum and the crystal structures of aluminum oxides in the pressure range of planetary interiors are not well established. Here, we predicted two aluminum suboxides (Al2O, AlO) and two superoxides (Al4O7, AlO3) with uncommon stoichiometries at high pressures using first-principle calculations and crystal structure prediction methods. We find that the P4/nmm Al2O becomes stable above ~765 GPa and may survive in the deep mantles or cores of giant planets such as Neptune. Interestingly, the Al2O and AlO are metallic and have electride features, in which some electrons are localized in the interstitials between atoms. We find that Al2O has an electrical conductivity one order of magnitude higher than that of iron under the same pressure-temperature conditions, which may influence the total conductivity of giant planets. Our findings enrich the high-pressure phase diagram of aluminum oxides and improve our understanding of the interior structure of giant planets.

Research Priorities on One Health: A Bibliometric Analysis.

Objective: One Health is an emerging research area that has received increasing attention globally. In this study, we aimed to explore the global research trend and hotspots of One Health and provide a reference for potential future research and practices. Methods: This was a bibliometric descriptive study of publications on One Health in four directions, including zoonotic diseases, antimicrobial resistance, food safety, and vector-borne infections. Publications from 2003 to 2021 were retrieved using the Scopus database on One Health, which were screened based on the PRISMA guidelines. Keywords were analyzed and visualized using VOSviewer software. Results: A total of 12,815 publications were included. The annual number of publications and those on each topic showed a gradual increase from 181 in 2003 to 1,647 in 2020, with an average annual growth rate of about 20.2%; the top three countries in terms of the number of publications were the United States of America (n=3,588), the United Kingdom (n=1,429) and China (n=1,233); the major research subjects were mainly in the natural sciences, with fewer social sciences subjects involved (n = 312; 1%). The main research directions within the area of zoonotic diseases included viral, bacterial, parasitic zoonotic diseases, and vector-borne diseases, with a small amount of antimicrobial resistance research. The major research interests within antimicrobial resistance were Enterobacteriaceae drug-resistant bacteria, methicillin-resistant Staphylococcus aureus, Pseudomonas aeruginosa, and antimicrobial resistance gene detection; research on food safety clustered around agronomy research, aquaculture research as well as a small amount of antimicrobial resistance research in food; and research on vector-borne diseases focused on mosquito-borne infectious diseases, tick-borne infectious diseases, and vectors. Conclusions: The scientific literature on One Health has witnessed a rising global trend. Most research has focused on the human-animal health interface, while environmental health is often neglected. Research subjects mainly fall within natural science disciplines, with less social science research. More support needs to be given to interdisciplinary and intersectoral cooperation and research in the future.

The governance of imported 2019-nCov infections: What can be learned from China's experience?

Delta and Omicron variants of 2019-nCoV are still spreading globally, and many imported infections have been identified in China as well. In order to control the spread chain from imported to local, China has implemented the dynamic Covid-zero policy. In this article we summarized China's governance models and practices of fighting potential imported infections in two directions. One targets at international travelers, which can be outlined as four lines of defense: customs epidemic prevention, quarantine upon arrival, relevant laws and regulations, and community tracking. The other is against other vectors potentially carrying 2019-nCoV, which can be outlined by three lines of defense: customs epidemic prevention, disinfection and personal protection, and information management. However, there are still some challenges that are yet to be addressed, such as illegal immigration, accidental occupational exposure to 2019-nCoV, etc. China's experience indicates that no country can stay safe during the global pandemic as long as there are local outbreaks in other countries, and active prevention and control measures based on science and a complete set of laws and regulations are still necessary at current stage. What's more, accountable government commitment and leadership, strengthened health and social governance systems, and whole society participation are required. It is suggested that the global community continue to closely cooperate together and take active rather than passive actions to block the potential imported 2019-nCoV from causing local spreading.

Superionic Silica-Water and Silica-Hydrogen Compounds in the Deep Interiors of Uranus and Neptune.

Silica, water, and hydrogen are known to be the major components of celestial bodies, and have significant influence on the formation and evolution of giant planets, such as Uranus and Neptune. Thus, it is of fundamental importance to investigate their states and possible reactions under the planetary conditions. Here, using advanced crystal structure searches and first-principles calculations in the Si-O-H system, we find that a silica-water compound (SiO_{2})_{2}(H_{2}O) and a silica-hydrogen compound SiO_{2}H_{2} can exist under high pressures above 450 and 650 GPa, respectively. Further simulations reveal that, at high pressure and high temperature conditions corresponding to the interiors of Uranus and Neptune, these compounds exhibit superionic behavior, in which protons diffuse freely like liquid while the silicon and oxygen framework is fixed as solid. Therefore, these superionic silica-water and silica-hydrogen compounds could be regarded as important components of the deep mantle or core of giants, which also provides an alternative origin for their anomalous magnetic fields. These unexpected physical and chemical properties of the most common natural materials at high pressure offer key clues to understand some abstruse issues including demixing and erosion of the core in giant planets, and shed light on building reliable models for solar giants and exoplanets.